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sure! in r, the `dplyr` package provides a useful function called `across()` that allows you to apply a function to multiple columns in a data frame. the `across()` function is particularly handy when you want to perform the same operation on several columns at once.

here's a step-by-step tutorial with a code example to demonstrate how to use the `across()` function:

1. first, you need to install and load the `dplyr` package if you haven't already. you can do this with the following code:



2. next, let's create a sample data frame to work with. for this example, we'll create a data frame with three columns: "a", "b", and "c".



3. now, let's use the `across()` function to add 10 to each value in columns "a", "b", and "c" simultaneously. we will use the `mutate()` function from `dplyr` along with `across()` to achieve this.



in the code above, the `across(c(a, b, c), ~ . + 10)` part specifies that we want to apply the function `~ . + 10` (which adds 10 to each value) across columns "a", "b", and "c".

that's it! you have successfully applied a function across multiple columns using the `across()` function in r. you can modify the function inside `across()` to perform different operations on the columns as needed.

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